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A bit odd that Pinecone is publishing this…

I can understand if they identified that building with LangChain means more Pinecone usage, and a barrier to building with Langchain is its documentation and ease of getting started, but if the now well funded project isn’t producing this itself (and in my own experience the Typescript library at least doesn’t feel like it’s hitting the nail on the head and I ended up reading source code) then I think that’s a sign we’re still searching for the best way to build complex things here



The fact that pinecone published this is proof of how many AI tooling products see Langchain as key to their distribution.

Personally, I find langchain unnecessary if you already know which tools you are going to use.

It remains to be seen how important portability of workloads and discoverability of tooling will be in this space. My experience with cloud computing has taught me that portability of workloads is overrated, but I'm not sure that lesson will translate well to AI models.


this is basic content marketing strategy, Pinecone can be used with LangChain and a decent chunk of people searching for tutorials about LangChain will indirectly learn about Pinecone as a result of this article


Twitter retweets and seo boost . Pinecone has an extensive content strategy


LangChain is undeniably the best option for building demos.


Vector stores and calculations of vector similarity are an adjacent complement to the ReAct workflow, not replacing it or being specific to LangChain.




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